Detecting student frustration based on handwriting behavior

Hiroki Asai, Hayato Yamana

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

Detecting states of frustration among students engaged in learning activities is critical to the success of teaching assistance tools. We examine the relationship between a student's pen activity and his/her state of frustration while solving handwritten problems. Based on a user study involving mathematics problems, we found that our detection method was able to detect student frustration with a precision of 87% and a recall of 90%. We also identified several particularly discriminative features, including writing stroke number, erased stroke number, pen activity time, and air stroke speed.

本文言語English
ホスト出版物のタイトルUIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology
ページ77-78
ページ数2
DOI
出版ステータスPublished - 2013 11 15
イベント26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013 - St. Andrews, United Kingdom
継続期間: 2013 10 82013 10 11

出版物シリーズ

名前UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology

Conference

Conference26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013
国/地域United Kingdom
CitySt. Andrews
Period13/10/813/10/11

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用
  • ソフトウェア

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